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Record W3122863622

The Effect of Education on Equity Holdings

2010· preprint· en· W3122863622 on OpenAlexaff
Dmytro Hryshko, María Luengo-Prado, Bent E. Sørensen

Bibliographic record

VenueRePEc: Research Papers in Economics · 2010
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRespondentEquity (law)Demographic economicsPanel dataPanel Study of Income DynamicsLabour economicsFixed effects modelEconomicsBusinessEconometricsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

We study the effect of education on equity ownership in the form of stocks or mutual funds (outside of retirement accounts). We find a causal effect of education on stockholding using the number of colleges in the county where the respondent grew up as an instrument and data from the Panel Study of Income Dynamics. The effect is particularly strong for whites from non-privileged backgrounds. We explore the channels through which education affects equity holdings using the Wisconsin Longitudinal Survey and find that, controlling for family fixed effects, increased cognition and features associated with having a white-collar job appear to be the Stock market participation in the United States and other advanced economies does not exceed 50 percent of households and recent research suggests that a “fixed cost ” of participation is the main reason why participation is not higher. Such fixed costs are likely due to unfamiliarity with stocks and not due to trading costs which have declined steeply

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.326
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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